Identification of secretory pathway-related genes based on Random Forest algorithm to predict the prognosis and immunotherapy response of hepatocellular carcinoma.

BACKGROUND: The dysfunction of secretory pathways may represent biomarkers or therapeutic targets of cancer. The hepatocellular carcinoma (HCC) phenotype was studied in relation to the genes in the secretory pathway and to screen for a combination of genes that may be a viable therapeutic target for HCC and connected to the pathophysiological features of the tumor. METHODS: Using the HCC information from The Cancer Genome Atlas, somatic mutation and prognostic association analysis were performed on the secretory pathway genes. Based on prognostic genes in the secretory pathway, the samples were consensus clustered, and a Random Forest model was built. The clinical characteristics, tumor mutation burden, functional status and potential responses to immunotherapy and tumor suppressor medications of various subtypes and risk groups were discussed. RESULTS: Of the 84 genes for secretory pathway, 32 were prognostic genes related to HCC, which divided HCC into two categories: C1 and C2. By comparing the two types of HCC samples, it was found that the survival outcome of C1 was inferior, with stronger adaptive and innate immunity, but less sensitive to immunotherapy than C2. The constructed prognostic signature included seven of the 32 prognostic genes in the secretory pathway, which showed significant correlation with the prognosis, somatic mutation, biological pathway status, potential response to immunotherapy and sensitivity of 72 tumor suppressor drugs from different HCC cohorts, and had a feasible prognostic effect for 31 types of cancer and immunotherapy cohorts. CONCLUSIONS: In this study, HCC was divided into two molecular subtypes according to prognostic genes in the secretory pathway, and seven of them were combined into one signature, which produced significant results in evaluating the prognosis of different HCC cohorts, pan-cancer cohorts and immunotherapy cohorts, and had potential guiding significance for prophylactic immunotherapy in patients with HCC.

Axial perspective to find the largest intraosseous space available for percutaneous screw fixation of fractures of the acetabular anterior column.

OBJECTIVE: To find the largest screw path in the acetabular anterior column using a novel method of axial perspective and test the clinical feasibility of the anterior column axial view projection. METHODS: 3D models with the inner triangular patches deleted were created from the pelvic CT scan data of 58 normal pelvises. The transparency of each 3D model was downgraded at the axial perspective (the view perpendicular to the cross section of the anterior column axis) so that a translucent area was seen clearly. The orientations of each 3D model were adjusted until a triangle-like translucent area that could accommodate the largest virtual screw (Screw I) was present and then an ellipse-like translucent area that could accommodate the two largest virtual screws (Screw II) was present. The maximum diameter, direction of Screw I and the maximum diameter Screw II were measured. Clinical feasibility of the axial view projection was next tested in five cadaveric specimens. RESULTS: The mean maximum diameters of Screw I and Screw II were 11.20 ± 1.73 (7.80-14.60 mm) and 8.71 ± 0.91 (6.60-10.60 mm), respectively. The angles of Screw I to the transverse, coronal and sagittal planes were 41.16° ± 4.59°, 18.18° ± 1.15° and 44.33° ± 4.31°, respectively. Translucent areas were successfully observed in all the cadaveric hemi-pelves and guide pins were successfully inserted in all the cadaveric hemi-pelves with the assistance of the anterior column axial view projection without cortex penetration or joint violation. CONCLUSIONS: The acetabular anterior column could safely accommodate not only one 7.3-mm screw, but also two 6.5-mm screws. The anterior column axial projection may be clinically feasible.